df-db-connector 0.2.0

[There](https://github.com/deepmipt/dialog_flow_db_connector) is an addon for the [Dialog Flow Framework](https://github.com/deepmipt/dialog_flow_engine), a minimalistic open-source engine for conversational services.

Dialog Flow DB Connector

There is an addon for the Dialog Flow Framework, a minimalistic open-source engine for conversational services.

Dialog Flow DB Connector allows you to to save and retrieve user dialogue states (in the form of a Context object) using various database backends.

Currently, the supported options are:

• json
• pickle
• shelve
• Sqlite
• Postgresql
• MySQL
• MongoDB
• Redis
• YDB

Aside from this, we offer some interfaces for saving data to your local file system. These are not meant to be used in production, but can be helpful for prototyping your application.

Quick Start

Installation

pip install df-db-connector

Please, note that if you are going to use one of the database backends, you will have to specify an extra or install the corresponding requirements yourself.

pip install df-db-connector[redis]
pip install df-db-connector[mongodb]
pip install df-db-connector[mysql]
pip install df-db-connector[postgresql]
pip install df-db-connector[sqlite]
pip install df-db-connector[ydb]

Basic example

from df_engine.core import Context, Actor
from df_db_connector import SQLConnector
from .script import some_df_script

db = SQLConnector("postgresql://user:password@host:port/dbname")

actor = Actor(some_df_script, start_label=("root", "start"), fallback_label=("root", "fallback"))


def handle_request(request):
user_id = request.args["user_id"]
if user_id not in db:
context = Context(id=user_id)
else:
context = db[user_id]
new_context = actor(context)
db[user_id] = new_context
assert user_id in db
return new_context.last_response

To get more advanced examples, take a look at examples on GitHub.

Contributing to the Dialog Flow DB Connector

Please refer to CONTRIBUTING.md.